Zhou Le-Ting, Qiu Shen, Lv Lin-Li, Li Zuo-Lin, Liu Hong, Tang Ri-Ning, Ma Kun-Ling, Liu Bi-Cheng
Kidney Blood Press Res. 2018;43(2):568-581. doi: 10.1159/000488830. Epub 2018 Apr 6.
BACKGROUND/AIMS: Chronic kidney disease (CKD) is a worldwide public health problem. Regardless of the underlying primary disease, CKD tends to progress to end-stage kidney disease, resulting in unsatisfactory and costly treatment. Its common pathogenesis, however, remains unclear. The aim of this study was to provide an unbiased catalog of common gene-expression changes of CKD and reveal the underlying molecular mechanism using an integrative bioinformatics approach.
We systematically collected over 250 Affymetrix microarray datasets from the glomerular and tubulointerstitial compartments of healthy renal tissues and those with various types of established CKD (diabetic kidney disease, hypertensive nephropathy, and glomerular nephropathy). Then, using stringent bioinformatics analysis, shared differentially expressed genes (DEGs) of CKD were obtained. These shared DEGs were further analyzed by the gene ontology (GO) and pathway enrichment analysis. Finally, the protein-protein interaction networks(PINs) were constructed to further refine our results.
Our analysis identified 176 and 50 shared DEGs in diseased glomeruli and tubules, respectively, including many transcripts that have not been previously reported to be involved in kidney disease. Enrichment analysis also showed that the glomerular and tubulointerstitial compartments underwent a wide range of unique pathological changes during chronic injury. As revealed by the GO enrichment analysis, shared DEGs in glomeruli were significantly enriched in exosomes. By constructing PINs, we identified several hub genes (e.g. OAS1, JUN, and FOS) and clusters that might play key roles in regulating the development of CKD.
Our study not only further reveals the unifying molecular mechanism of CKD pathogenesis but also provides a valuable resource of potential biomarkers and therapeutic targets.
背景/目的：慢性肾脏病（CKD）是一个全球性的公共卫生问题。无论潜在的原发性疾病如何，CKD都倾向于进展为终末期肾病，导致治疗效果不佳且费用高昂。然而，其常见的发病机制仍不清楚。本研究的目的是提供一个关于CKD常见基因表达变化的无偏目录，并使用综合生物信息学方法揭示潜在的分子机制。
我们系统地收集了超过250个来自健康肾组织以及患有各种类型确诊CKD（糖尿病肾病、高血压肾病和肾小球肾病）的肾小球和肾小管间质部分的Affymetrix微阵列数据集。然后，通过严格的生物信息学分析，获得了CKD的共享差异表达基因（DEGs）。这些共享的DEGs通过基因本体（GO）和通路富集分析进一步分析。最后，构建蛋白质-蛋白质相互作用网络（PINs）以进一步完善我们的结果。
我们的分析分别在患病的肾小球和肾小管中鉴定出176个和50个共享的DEGs，包括许多先前未报道与肾病相关的转录本。富集分析还表明，在慢性损伤过程中，肾小球和肾小管间质部分经历了广泛的独特病理变化。正如GO富集分析所揭示的，肾小球中的共享DEGs在外泌体中显著富集。通过构建PINs，我们鉴定出了几个可能在调节CKD发展中起关键作用的枢纽基因（如OAS1、JUN和FOS）和簇。
我们的研究不仅进一步揭示了CKD发病机制的统一分子机制，还提供了潜在生物标志物和治疗靶点的宝贵资源。
